Mlprodict

==============================

* 289: Avoids raising an exception when an optional parameter is not specified (2021-07-26)
* 288: Extends code coverage (2021-07-25)
* 287: Adds python runtime for operator Loop, SequenceInsert, ConcatFromSequence (2021-07-25)
* 286: Adds runtime for operator Range (2021-07-13)

==============================

* 285: Adds function cst to create constant with numpy API for ONNX (2021-07-12)
* 283: Commutative property (2021-07-12)
* 281: Infers temporary allocation needed while computing the outputs (2021-07-12)
* 284: Adds function transpose to numpy API for ONNX (2021-07-10)
* 282: Upgrade requirements to skl2onnx>=1.9.0 (2021-07-02)
* 280: More robustness for the python runtime (2021-07-01)
* 279: Implements method infer_types in OnnxInference (2021-06-28)
* 278: Adds operators ReduceSum, Max to OnnxMicroRuntime (2021-06-27)
* 277: Switch to python 3.9 in CI (2021-06-25)
* 276: Use openmp to parallelize QLinearConv (2021-06-25)
* 275: Adds new strategy to pick up the best einsum equation based on ML (2021-06-25)
* 274: Fixes issue raised with scipy 1.7.0 (2021-06-22)
* 273: Adds operator where, improves numpy api (x[x<0]= 2) (2021-06-18)
* 272: Explore custom implementation of operator add (2021-06-18)
* 271: Updates default opset from 13 to 14 (2021-06-17)
* 270: Adds more tests for QLinearConv runtime (2021-06-16)
* 269: Adds runtime for operator QLinearConv (2021-06-04)
* 268: Adds function to prepare data for onnxruntime_perf_test (2021-05-17)
* 267: Moves onnxruntime code inside a wrapper to reduce logs (2021-05-14)
* 266: Optimizes einsum even if not decomposed (2021-05-13)
* 265: Refactoring, moves files to onnx_tools (2021-05-12)
* 264: Support SessionOptions for runtime onnxruntime2 (2021-05-12)
* 263: Refactor einsum files (2021-05-06)
* 262: Refactoring, moving files into onnx_tools (2021-05-06)
* 261: Improves einsum decomposition by using gemm and removing a transpose (2021-05-05)
* 260: New command line to benchmark einsum decomposition (2021-05-03)
* 259: Minor changes to Einsum decomposition (2021-05-02)
* 258: Decomposes Einsum into simple matrix operations (2021-04-30)
* 257: Fixes 256, add method to validate input data in numpy API for ONNX (2021-04-20)
* 256: Add virtual method to validate input before predictions in numpy API for ONNX (2021-04-20)

==============================

* 255: Supports any embedded estimator with numpy API (2021-04-17)
* 254: Adds python runtime for operator ReduceL1 (2021-04-16)
* 253: Adds runtime for operator ReduceL2 (2021-04-14)
* 252: Implements an experimental version of reducesum for the case RK (2021-04-07)
* 251: Increases code coverage (2021-04-07)
* 250: Increases code coverage of unit tests (2021-04-03)
* 248: Adds implementation of BatchNormalization opset 14 (2021-03-29)
* 247: Introduces FctVersion to fix issue with optional arguments (2021-03-29)
* 246: Extends example on ReduceSum benchmark (2021-03-26)
* 244: Supports embedded models, complete tutorial on numpy API for ONNX (2021-03-26)
* 243: Add decorator to wrap converter for clustering (numpy API) (2021-03-17)
* 242: Add decorator to wrap converter for classifier (numpy API) (2021-03-17)
* 241: Add decorator to register scikit-learn classes with numpy API for ONNX (2021-03-14)
* 240: Add decorator to wrap converter for regressor (numpy API) (2021-03-14)
* 239: Add runtime empty (2021-03-13)
* 238: Use numpy API for ONNX to write custom converters (2021-03-13)
* 237: Add a unit test to check an exception (2021-03-10)
* 236: Implements __setitem__ for one dimension array (2021-03-08)
* 235: Supports profiling for runtime onnxruntime1 (2021-03-04)
* 233: Extend documentation about numpy API for ONNX (2021-03-04)
* 234: Add parameter overwrite to select_model_inputs_outputs (2021-03-03)
* 232: Implements pickling for functions used in numpy API for ONNX (2021-03-03)
* 231: Supports different inputs in select_model_inputs_outputs (2021-03-03)
* 230: Add unsqueeze, squeeze, expand_dims to numpy API for ONNX (2021-03-02)
* 229: Add method flatten, function pad to numpy API for ONNX (2021-03-01)
* 228: Improves numpy API for ONNX: type constraints (2021-03-01)
* 227: Add functions arange, cumsum, compress to numpy API for ONNX (2021-03-01)
* 226: Add function Einsum to numpy API for ONNX (2021-02-28)
* 225: Adds function Clip to numpy API for ONNX (2021-02-28)
* 224: Adds functions ceil, round to numpy API for onnx (2021-02-27)
* 223: Test numpy API against onnxruntime (2021-02-27)
* 222: Add hyperbolic function, prod, mean, argmin, argmax (2021-02-26)
* 221: Add many simple functions to numpy API for ONNX (2021-02-26)
* 220: Tutorial on numpy API for ONNX (2021-02-26)
* 219: Simplifies onnxfication of FunctionTransformer (2021-02-23)
* 218: Implements __setitem__ for class OnnxVar (2021-02-21)
* 217: Move custom operator to a specific method easier to maintain (2021-02-21)
* 216: Fix crash with Gather, TopK when k=0 or indices is empty. (2021-02-20)
* 215: Implements __getitem__ for OnnxVar (onnxnumpy) (2021-02-20)
* 214: Implements numpy functions with onnx (2021-02-19)
* 213: Add parameter show to plot_onnx. (2021-02-11)
* 212: Fixes 210, check first models from zoo, fix operator conv when B is not null (2021-02-05)
* 210: Investigate models from ONNX zoo (2021-02-05)
* 211: numpy 1.20 does not allow nan values in int64 arrays any more, fix a unit test about imputer (2021-02-02)
* 208: Add try catch around import in asv benchmark (2021-01-30)
* 207: Reduces greater batch size to 10.000 instead of 100.000. (2021-01-29)
* 205: Fixes asv configuration (2021-01-18)
* 206: Build wheel for all many platforms in CI (2021-01-17)

==============================

* 203: Enable Python 3.9, enable opset 13, upgrade version number (2021-01-04)
* 202: Enable opset 13 (ONNX) (2021-01-04)
* 201: Fixes 200, add support for float16 (2020-12-30)
* 200: Add support for bfloat16 (2020-12-30)
* 199: Fix unit tests recently failing due to onnxruntime update. (2020-12-15)

==============================

* 196: Fixes operator Slice for opset 9 (2020-12-11)
* 198: Fixes 197, add function to plot onnx graph with matplotlib (2020-12-09)
* 197: Add a function to plot an onnx graph into matplotlib (2020-12-09)
* 195: Fixes 194, add function to add an operator in the graph (2020-12-08)
* 194: Add a function to insert a cast operator between two nodes (2020-12-08)
* 193: Improves notebook coverage, update CI (2020-11-29)
* 192: Fixes 191, improves performance of TreeEnsemble (2020-11-28)
* 191: Improves performance of TreeEnsemble (2020-11-28)
* 190: Fixes 189, parallelization of Einsum (2020-11-17)
* 189: Introduce parallelization in experimental einsum implementation (2020-11-17)
* 188: Fixes 187, custom implementation for operator Einsum (2020-11-15)
* 187: Custom implementation for operator Einsum (2020-11-15)
* 186: Fixes 185, add operator LessOrEqual (2020-11-15)
* 185: Add operator LessOrEqual (2020-11-15)
* 181: Fix converter xgboost when ntree_limit is set up (2020-11-14)
* 184: Fixes 183, fix missing parameter black_op in OnnxPipeline (2020-11-07)
* 183: Fix error in OnnxPipeline, parameter black_op not found (2020-11-07)
* 182: Fixes 178, fix xgboost issue with ntree_limit (2020-11-07)
* 178: Fixes unit test testing OnnxConv (issue with shapes) (2020-11-07)
* 180: Fixes 179, fix guess_schema_from_data for categories (2020-11-03)
* 179: guess_schema_data_type fails with category in dataframe (2020-11-03)
* 176: Fixes 175, add operator dropout (2020-09-29)
* 175: Add operator Dropout (2020-09-29)
* 174: Add support for ReduceSum >= 13 (2020-09-21)
* 173: Fixes 172, add runtime for operator MaxPool (2020-09-16)
* 172: Add runtime for operator MaxPool (2020-09-16)
* 171: Fixes 170, add operator Pad (2020-09-10)
* 170: Add runtime for operator Pad (2020-09-10)
* 169: fix compiling issue with ubuntu 16.04 (2020-09-03)
* 167: Add runtime for Operator Or (2020-08-25)
* 166: Add runtime for operator And (2020-08-25)
* 165: Add runtime for operator GreaterOrEqual (2020-08-25)
* 164: Add runtime for operator If (2020-08-25)
* 163: Add runtime for operator Unsqueeze (2020-08-25)
* 162: Add runtime for operator Split (2020-08-25)
* 161: Add support for disable_optimisation (2020-08-12)
* 160: Fixes 159, add operator ConvTranspose, refactoring. (2020-08-07)
* 159: Implements runtime for ConvTranspose (2020-08-07)
* 158: Fixes benchmark import issues (2020-08-03)
* 157: Simplify scenarios, reduce time for benchmark. (2020-08-02)
* 156: Fixes 155, improves documentation (2020-08-02)
* 155: Fixes API on documentation (2020-08-02)
* 154: Fixes y_train dtype for most of the problems. Fixes subproblems with GridSearchCV (2020-07-31)
* 153: Fixes 152, set set n_jobs to the number of CPU (2020-07-31)
* 152: Set n_jobs to the number of core - 1 when doing benchmark (2020-07-31)
* 151: Force operator Conv to use continuous array (2020-07-30)
* 150: Fixes nan issue in operator conv (2020-07-29)
* 147: Fixes 145, 150, shape inference for operator Conv (2020-07-29)
* 145: Fixes missing shape inference for operator conv (2020-07-29)
* 149: Fixes 148, add operator Atan (2020-07-22)
* 148: Add operator atan (2020-07-22)
* 146: Fixes 144, add operator GlobalAveragePool (2020-07-21)
* 144: Implements operator GlobalAveragePool (2020-07-21)
* 143: Fixes 142, add operator BatchNormalization (2020-07-21)
* 142: Implement python runtime for operator BatchNormalization (2020-07-21)
* 141: Fixes 140, add runtime for QuantizeLinear, DequantizeLinear (2020-07-20)
* 140: Implement runtime for QuantizeLinear, DequantizeLinear (2020-07-20)
* 139: Add runtime for operator EyeLike (2020-07-08)
* 138: Add code to register custom python operator (2020-07-08)
* 137: Remove parameter dtype (onnx conversion) (2020-07-08)
* 136: Add parameter reshape to OnnxTransformer (2020-07-03)
* 135: Add a function to change the first dimension output (ONNX). (2020-07-03)
* 133: Implements runtime for operator Gather (ONNX) (2020-06-18)
* 132: Add operator StringNormalizer, Tokenizer, TfidfVectorizer (ONNX) (2020-06-15)
* 131: Add custom operator solve (2020-06-12)
* 130: Add operator Erf (ONNX) (2020-06-11)
* 129: Add operator Einsum (ONNX) (2020-06-11)
* 128: Fixes 127, implements OnnxPipeline, train, convert at each step (2020-06-08)
* 127: Implements a pipeline which replaces early stages by onnx (2020-06-08)
* 123: Enables opset 12 (ONNX) (2020-06-04)
* 117: Support for op_version in onnx grammar (2020-06-04)
* 126: Fix xgboost converter for xgboost >= 1.0 (2020-05-18)
* 125: Refactor rewritten sklearn operators (2020-05-18)
* 124: Fixes 122, capture standard C ouptput with dump_data_model, first step for 123 (2020-05-16)
* 122: Captures C output when calling dump_data_and_model (2020-05-16)
* 121: Add function to convert array to bytes and bytes to array (onnx tensor) (2020-04-30)
* 120: Fix discrepencies for SVM classifier (ONNX) (2020-04-30)
* 119: Keep order in topk implementation (2020-04-17)
* 118: opset is not propagated in OnnxTransformer (2020-04-09)
* 115: Add a function to replay a benchmark when this one was dumped (more accurate) (2020-04-06)
* 116: Makes ZipMapDictionary picklable (2020-03-30)
* 114: Add more parameters to specify benchmark time (2020-03-30)
* 113: Add operators for opset 12 (2020-03-26)
* 112: Number of feature is wrong for problem num-tr-clus (2020-03-20)
* 111: Reduce the number of allocation in TreeEnsemble when it is parallelized (cache) (2020-03-13)
* 110: Implements runtime for operator Constant-12 (2020-03-06)
* 109: Generate a benchmark with asv to compare different runtime. Update modules in asv. (2020-03-06)
* 108: Add a function to reduce the memory footprint (2020-02-25)
* 106: Add operator Neg (2020-02-25)
* 101: Fix DecisionTreeClassifier disappearance on the benchmark graph (2020-02-25)
* 107: Add operator IsNaN (2020-02-24)
* 105: Support string labels for Linear, TreeEnsemble, SVM classifiers. (2020-02-24)
* 104: Enable / disable parallelisation in topk (2020-02-23)
* 103: Implements plot benchmark ratio depending on two parameters (2020-02-22)
* 102: Fix conversion for xgboost 1.0 (2020-02-21)
* 100: add notebook on TreeEnsemble (2020-02-19)
* 99: Fixes 93, use same code for TreeEnsembleClassifier and TreeEnsembleRegression (2020-02-19)
* 93: Use pointer for TreeClassifier (2020-02-19)
* 98: mlprodict i broken after onnxruntime, skl2onnx update (2020-02-15)
* 97: Add runtime for operator Conv (2020-01-24)
* 96: Fixes 97, add runtime for operator Conv (2020-01-24)
* 95: Fix OnnxInference where an output and an operator share the same name (2020-01-15)
* 94: Raw scores are always positive for TreeEnsembleClassifier (binary) (2020-01-13)
* 90: Implements a C++ runtime for topk (2019-12-17)
* 86: Use pointers to replace treeindex in tree ensemble cpp runtime (2019-12-17)
* 92: Implements a C++ version of ArrayFeatureExtractor (2019-12-14)
* 89: Implements a function which extracts some informations on the models (2019-12-14)
* 88: Fix bug in runtime of GatherElements (2019-12-14)
* 87: Add converter for HistGradientBoostRegressor (2019-12-09)
* 85: Implements a precompiled run method in OnnxInference (runtime='python_compiled') (2019-12-07)
* 84: Automatically creates files to profile time_predict function in the benchmark with py-spy (2019-12-04)
* 83: ONNX: includes experimental operators in the benchmark (2019-12-04)
* 82: Function translate_fct2onnx: use of opset_version (2019-12-04)
* 81: ONNX benchmark: track_score returns scores equal to 0 or 1 (unexpected) (2019-12-04)
* 80: ONNX: extend benchmark to decision_function for some models (2019-12-03)
* 77: Improves ONNX benchmark to measure zipmap impact. (2019-12-03)
* 76: Implements ArgMax 12, ArgMax 12 (python onnx runtime) (2019-11-27)
* 75: ONNX: fix random_state whevever it is available when running benchmark (2019-11-27)
* 59: ONNX: Investigate kmeans and opset availability. (2019-11-21)
* 66: ONNX: improves speed of python runtime for decision trees (2019-11-19)
* 74: Function _modify_dimension should return the same dataset if called the same parameter (even if it uses random functions) (2019-11-15)
* 73: ONNX: fix links on benchmark page (opset is missing) (2019-11-07)
* 72: ONNX: support of sparse tensor for a unary and binary python operators (2019-11-06)
* 71: ONNX: add operator Constant (2019-11-06)
* 67: ONNX: improves speed of svm regressor (2019-11-06)
* 70: ONNX: write tools to test convervsion for models in scikit-learn examples (2019-10-29)
* 65: ONNX: investigate discrepencies for k-NN (2019-10-28)
* 69: ONNX: side by side should work by name and not by positions (2019-10-23)
* 68: ONNX: improves speed of SGDClassifier (2019-10-23)
* 61: Implements a function to create a benchmark based on asv (ONNX) (2019-10-17)
* 63: Export asv results to csv (ONNX) + command line (2019-10-11)
* 64: Add an example with lightgbm and categorical variables (ONNX) (2019-10-07)
* 62: Implements command line for the asv benchmark (ONNX) (2019-10-04)
* 60: Improve lightgbm converter (ONNX) (2019-09-30)
* 58: Fix table checking model, merge is wrong in documentation (2019-09-20)
* 57: ONNX: handles dataframe when converting a model (2019-09-15)
* 56: ONNX: implements cdist operator (2019-09-12)
* 54: ONNX: fix summary, it produces multiple row when model are different when opset is different (2019-09-12)
* 51: ONNX: measure the time performance obtained by using optimization (2019-09-11)
* 52: ONNC-cli: add a command line to optimize an onnx model (2019-09-10)
* 49: ONNX optimization: remove redundant subparts of a graph (2019-09-09)
* 48: ONNX optimization: reduce the number of Identity nodes (2019-09-09)
* 47: Implements statistics on onnx graph and sklearn models, add them to the documentation (2019-09-06)
* 46: Implements KNearestNeibhorsRegressor supporting batch mode (ONNX) (2019-08-31)
* 45: KNearestNeighborsRegressor (2019-08-30)
* 44: Add an example to look into the performance of every node for a particular dataset (2019-08-30)
* 43: LGBMClassifier has wrong shape (2019-08-29)
* 42: Adds a graph which visually summarize the validating benchmark (ONNX). (2019-08-27)
* 41: Enables to test multiple number of features at the same time (ONNX) (2019-08-27)
* 40: Add a parameter to change the number of featuress when validating a model (ONNX). (2019-08-26)
* 39: Add a parameter to dump all models even if they don't produce errors when being validated (ONNX) (2019-08-26)
* 24: support double for TreeEnsembleClassifier (python runtime ONNX) (2019-08-23)
* 38: See issue on onnxmltools. https://github.com/onnx/onnxmltools/issues/321 (2019-08-19)
* 35: Supports parameter time_kwargs in the command line (ONNX) (2019-08-09)
* 34: Add intervals when measuring time ratios between scikit-learn and onnx (ONNX) (2019-08-09)
* 31: Implements shape inference for the python runtime (ONNX) (2019-08-06)
* 15: Tells operator if the execution can be done inplace for unary operators (ONNX). (2019-08-06)
* 27: Bug fix (2019-08-02)
* 23: support double for TreeEnsembleRegressor (python runtime ONNX) (2019-08-02)
* 26: Tests all converters in separate processeses to make it easier to catch crashes (2019-08-01)
* 25: Ensures operator clip returns an array of the same type (ONNX Python Runtime) (2019-07-30)
* 22: Implements a function to shake an ONNX model and test float32 conversion (2019-07-28)
* 21: Add customized converters (2019-07-28)
* 20: Enables support for TreeEnsemble operators in python runtime (ONNX). (2019-07-28)
* 19: Enables support for SVM operators in python runtime (ONNX). (2019-07-28)
* 16: fix documentation, visual graph are not being rendered in notebooks (2019-07-23)
* 18: implements python runtime for SVM (2019-07-20)
* 17: add a mechanism to use ONNX with double computation (2019-07-15)
* 13: add automated benchmark of every scikit-learn operator in the documentation (2019-07-05)
* 12: implements a way to measure time for each node of the ONNX graph (2019-07-05)
* 11: implements a better ZipMap node based on dedicated container (2019-07-05)
* 8: implements runtime for decision tree (2019-07-05)
* 7: implement python runtime for scaler, pca, knn, kmeans (2019-07-05)
* 10: implements full runtime with onnxruntime not node by node (2019-06-16)
* 9: implements a onnxruntime runtime (2019-06-16)
* 6: first draft of a python runtime for onnx (2019-06-15)
* 5: change style highlight-ipython3 (2018-01-05)